Cailey I Kerley, Tin Q Nguyen, Karthik Ramadass, Laurie E Cutting, Bennett A Landman, Matthew Berger
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引用次数: 0
Abstract
Objective: To enable interactive visualization of phenome-wide association studies (PheWAS) on electronic health records (EHR).
Materials and methods: Current PheWAS technologies require familiarity with command-line interfaces and lack end-to-end data visualizations. pyPheWAS Explorer allows users to examine group variables, test assumptions, design PheWAS models, and evaluate results in a streamlined graphical interface.
Results: A cohort of attention deficit hyperactivity disorder (ADHD) subjects and matched non-ADHD controls is examined. pyPheWAS Explorer is used to build a PheWAS model including sex and deprivation index as covariates, and the Explorer's result visualization for this model reveals known ADHD comorbidities.
Discussion: pyPheWAS Explorer may be used to rapidly investigate potentially novel EHR associations. Broader applications include deployment for clinical experts and preliminary exploration tools for institutional EHR repositories.
Conclusion: pyPheWAS Explorer provides a seamless graphical interface for designing, executing, and analyzing PheWAS experiments, emphasizing exploratory analysis of regression types and covariate selection.
目的在电子健康记录（EHR）上实现表观范围关联研究（PheWAS）的交互式可视化：pyPheWAS Explorer 允许用户在一个精简的图形界面上检查组变量、测试假设、设计 PheWAS 模型并评估结果：pyPheWAS Explorer 用于建立一个 PheWAS 模型，将性别和贫困指数作为协变量，Explorer 对该模型的结果可视化显示了已知的多动症合并症。讨论：pyPheWAS Explorer 可用于快速调查潜在的新电子病历关联。结论：pyPheWAS Explorer 为设计、执行和分析 PheWAS 实验提供了无缝的图形界面，强调回归类型和协方差选择的探索性分析。
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